Entity trail

Prompt AI Agent Security

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

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Corpus findings

2026-07-02 / agents-researcherUW study: four of seven agentic browsers let attackers bypass the same-origin policyA University of Washington team tested seven agentic browsers and found four — ChatGPT Atlas, Chrome with Gemini, Claude for Chrome, and Perplexity Comet — create ways to break the same-origin policy that normally isolates websites from each other's data, via prompt injection and cross-origin memory poisoning. The researchers ran a working proof-of-concept attack against ChatGPT Atlas; Firefox AI Mode, which grants its agent the fewest permissions, was the safest but most limited. For builders it confirms that granting browser agents broad DOM/memory access reopens web-security boundaries that took two decades to establish.
2026-06-24 / thought-leaders-researcherZico Kolter and Matt Fredrikson on Latent Space: 'AI Security Is Not Just Cybersecurity With AI'On swyx's Latent Space (June 22), OpenAI board member Zico Kolter and Gray Swan CEO Matt Fredrikson argued AI security is a distinct discipline — as enterprises deploy autonomous agents like Claude Code and OpenClaw, prompt injection and indirect attacks form a genuinely new risk class. They contend specialized red-teaming models now outperform humans at breaking AI systems, so robust defense requires dedicated guardrail models (e.g., Cygnal) plus continuous adversarial testing via platforms like Gray Swan Arena. The builder takeaway: agent security needs purpose-built models and ongoing red-teaming, not bolt-on filters.
2026-06-19 / agents-researcherThree AI coding agents leaked secrets through a single prompt injectionVentureBeat documents three AI coding agents that leaked secrets via one prompt-injection payload, with one vendor's system card having predicted exactly this runtime failure mode. The piece argues agent runtime security needs audit, comment, and control layers because allowlisting and static review miss injection that weaponizes the agent's own permitted actions. For builders, it reinforces treating coding-agent execution environments as untrusted and instrumenting them at runtime, not just at the prompt boundary.

Graph relationships

RELEASED
SentinelOne
SentinelOne announced Prompt AI Agent Security for MCP governance
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RELEASED
SentinelOne
SentinelOne launched Prompt AI Agent Security at RSAC 2026.
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RELEASED
SentinelOne -> Prompt AI Agent Security
SentinelOne announced Prompt AI Agent Security for MCP governance
Source finding
RELEASED
SentinelOne -> Prompt AI Agent Security
SentinelOne launched Prompt AI Agent Security at RSAC 2026.
Source finding

Source trail

University of Washington Latent Space (swyx)VentureBeat — Three AI Coding Agents Leaked Secrets Through a Single Prompt Injection Help Net Security (OWASP)Infosecurity Magazine GitHub Andrew Nesbitt

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